Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/150294
Title: On reliability analysis of smart grids under topology attacks : a stochastic Petri net approach
Authors: Li, Beibei
Lu, Rongxing
Choo, Raymond Kim-Kwang
Wang, Wei
Luo, Sheng
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2018
Source: Li, B., Lu, R., Choo, R. K., Wang, W. & Luo, S. (2018). On reliability analysis of smart grids under topology attacks : a stochastic Petri net approach. ACM Transactions On Cyber-Physical Systems, 3(1), 10-. https://dx.doi.org/10.1145/3127021
Journal: ACM Transactions on Cyber-Physical Systems
Abstract: Building an efficient, smart, and multifunctional power grid while maintaining high reliability and security is an extremely challenging task, particularly in the ever-evolving cyber threat landscape. The challenge is also compounded by the increasing complexity of power grids in both cyber and physical domains. In this article, we develop a stochastic Petri net based analytical model to assess and analyze the system reliability of smart grids, specifically against topology attacks under system countermeasures (i.e., intrusion detection systems and malfunction recovery techniques). Topology attacks, evolving from false data injection attacks, are growing security threats to smart grids. In our analytical model, we define and consider both conservative and aggressive topology attacks, and two types of unreliable consequences (i.e., system disturbances and failures). The IEEE 14-bus power system is employed as a case study to clearly explain the model construction and parameterization process. The benefit of having this analytical model is the capability to measure the system reliability from both transient and steady-state analysis. Finally, intensive simulation experiments are conducted to demonstrate the feasibility and effectiveness of our proposed model.
URI: https://hdl.handle.net/10356/150294
ISSN: 2378-962X
DOI: 10.1145/3127021
Schools: School of Electrical and Electronic Engineering 
Rights: © 2018 ACM. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:EEE Journal Articles

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